Within the meaning of this specification, the term “key figure” broadly refers to any quantifiable attribute of a tangible or intangible object that can change or vary over time. The time dependent behavior of such a key figure is usually monitored by means of computer systems. A few examples of key figures include: a temperature, a distance of two objects, a weight of an object, an area volume of a building under construction, an area under cultivation, the number of employees of a company, the area used for administration or production or for stock within an organization, the number of PC workplaces or the like within a company, market shares of products or product families, turnover per employee, personnel costs per employee, and so on. Key figures, which are used to characterize non-financial data of an organization or a sub-unit of an organization are frequently referred to as statistical key figures.
Key figures are usually stored in a computer system. This may be achieved by storing the value of the key figure at a certain point in time into a data structure or field and assigning the date of that certain point of time to the data field.
However, problems arise, if a specific key figure needs to be evaluated over different, overlapping time periods. For example, an area of cultivation may need to be evaluated for different fiscal periods of different countries. In this example, the values of the key figure have to be stored independently for each fiscal period in order to avoid inconsistencies. This may require a huge amount of storage and involve a high level of administrative work, particularly if many key figures have to be monitored for many different evaluation periods, thus stressing system performance.
With enterprise resource planning (ERP) software, it is common practice to evaluate the financial situation of an enterprise by using several parallel ledgers. For each accounting area and ledger, different overlapping evaluation periods may exist. Thus, the data of a key figure must be persisted per accounting area and per ledger, thereby increasing the data volume per ledger.
In view of the foregoing, there is a need for improved methods, software applications and/or data processing systems that can provide, for example, efficient solutions to one or more the problems described above. Moreover, there is a need for improved solutions including software applications that provide a mechanism for monitoring key figures more efficiently.
The above description is based on the knowledge of the present inventors and not necessarily that known in the art.